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| import gradio as gr | |
| # To solve problems with pathlib in load_learner | |
| import pathlib | |
| import platform | |
| plt = platform.system() | |
| if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath | |
| from fastai.vision.all import load_learner, PILImage | |
| learn = load_learner('model.pkl') | |
| labels = learn.dls.vocab | |
| def predict(img): | |
| img = PILImage.create(img) | |
| pred,pred_idx,probs = learn.predict(img) | |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
| title = "Panettone or Pandoro?" | |
| description = "A prototype classifier developed with fastaiwith images from ddg." | |
| examples = [r'examples/panettone_01.jpg', | |
| r'examples/panettone_02.jpg', | |
| r'examples/pandoro_01.jpg', | |
| r'examples/pandoro_02.jpg' | |
| ] | |
| title = "Panettone or Pandoro?" | |
| demo = gr.Interface(fn=predict, inputs="image", | |
| outputs="label", | |
| examples=examples, | |
| title = title ) | |
| demo.launch() |